Bibliography - M. Dobossy

1. Court, Benjamin, K. W. Bandilla, Michael Celia, Thomas A. Buscheck, Jan M. Nordbotten, M. Dobossy, and Adam Janzen, 2012: Initial evaluation of advantageous synergies associated with simultaneous brine production and CO₂ geological sequestration. International Journal of Greenhouse Gas Control, Elsevier, 8, doi:10.1016/j.ijggc.2011.12.009 90-100
   [ Abstract ]

   Mitigation of global atmospheric carbon emissions requires a worldwide ramping up of CO₂ capture and sequestration (CCS) implementation in the next decades. While CCS could be deployed in isolation, there is also the possibility to consider CO₂ injection within a much broader framework of reservoir and resource management including active water (brine) management. The goal of this study is to provide an initial analysis of three identified synergies related to active brine management in CCS operations. The potential advantages of coupling simultaneous brine production to a large-scale CO₂ geological sequestration operation are explored through three separate modeling studies. Our results demonstrate that brine production can provide important pressure-control benefits, including increased injectivity potential through reduction of the injection well pressure, significant reduction of the extent of the Area of Review, within which operators must procure property rights and monitor and remediate potential leakage pathways, and reduction in the risk of CO₂ and brine leakage. The latter is especially important in reservoirs, like many in North America, where a significant number of potential leakage pathways, particularly abandoned wells, may exist within the Area of Review. We also observe that brine production has minimal impact on the overall shape of the CO₂ plume, with plume shape and extent strongly governed by formation parameters.

2. Nogues, J. P., Benjamin Court, M. Dobossy, Jan M. Nordbotten, and Michael Celia, 2012: A methodology to estimate maximum probable leakage along old wells in a geological sequestration operation. International Journal of Greenhouse Gas Control, Elsevier, 7, doi:10.1016/j.ijggc.2011.12.003 39-47
   [ Abstract ]

   This study presents a computational methodology to estimate the maximum probable leakage of CO₂ along old wells in a geological sequestration operation. The methodology quantifies the maximum probable CO₂ leakage as a function of the statistical characterization of existing wells. We use a Monte Carlo approach based on a computationally efficient simulator to run many thousands of realizations. Results from the Monte Carlo simulations are used to determine maximum leakage rates at 95% confidence. Uncertainty in the analysis is due to leaky well parameters, which are known to be highly uncertain. We consider a wide range of parameter values, with our focus on assignment of effective well permeability values and the correlation of those values along individual wells. We use a specific location in Alberta, Canada, to demonstrate the methodology using a hypothetical injection and an assumed probability structure for the well permeabilities. We show that for a wide range of parameter values, the amount of leakage is within the bounds suggested as acceptable for climate change mitigation.

3. Celia, Michael, Jan M. Nordbotten, Benjamin Court, M. Dobossy, and S. Bachu, 2011: Field-scale application of a semi-analytical model for estimation of CO₂ and brine leakage along old wells. International Journal of Greenhouse Gas Control, Elsevier, (5), doi:10.1016/j.ijggc.2010.10.005
   [ Abstract ]

   Carbon capture and geological storage (CCS) operations will require an environmental risk analysis to determine, among other things, the risk that injected CO₂ or displaced brine will leak from the injection formation into other parts of the subsurface or surface environments. Such an analysis requires site characterization including identification of potential leakage pathways. In North America, the century-long legacy of oil and gas exploration and production has left millions of oil and gas wells, many of which are co-located with otherwise good geological storage sites. Potential leakage along existing wells, coupled with layered stratigraphic sequences and highly uncertain parameters, makes quantitative analysis of leakage risk a significant computational challenge. However, new approaches to modeling CO₂ injection, migration, and leakage allow for realistic scenarios to be simulated within a probabilistic framework. Using a specific field site in Alberta, Canada, we perform a range of computational studies aimed at risk analysis with a focus on CO₂ and brine leakage along old wells. The specific calculations focus on the injection period, when risk of leakage is expected to be largest. Specifically, we simulate 50 years of injection of supercritical CO₂ and use a Monte Carlo framework to analyze the overall system behavior. The simulations involve injection, migration, and leakage over the 50-year time horizon for domains of several thousand square kilometers having multiple layers in the sedimentary succession and several thousand old wells within the domain. Because we can perform each simulation in a few minutes of computer time, we can run tens of thousands of simulations and analyze the outputs in a probabilistic framework. We use these kinds of simulations to demonstrate the importance of residual brine saturations, the range of current options to quantify leaky well properties, and the impact of depth of injection and how it relates to leakage risk.

4. Dobossy, M., Michael Celia, and Jan M. Nordbotten, 2011: An Efficient Software Framework for Performing Industrial Risk Assessment of Leakage for Geological Storage of CO₂. International Conference on Greenhouse Gas Technologies (GHGT 10), Elsevier/Energy Procedia, doi:10.1016/j.egypro.2011.02.368 4207-4214
   [ Abstract ]

   In response to anthropogenic CO₂ emissions, geological storage has emerged as a practical and scalable bridge technology while renewables and other environmentally friendly energy production methods mature. While an attractive solution, geological storage of CO₂ has inherent risk. Two primary concerns are recognized: 1) leakage of CO₂through caprock imperfections, and 2) brine displacement resulting in contamination of drinking water sources. Three mechanisms for both CO₂ and brine leakage have been identified: diffuse leakage through the caprock, leakage through faults and fractures in the caprock, and finally, leakage through man-made pathways such as abandoned wells from oil and gas exploration. While the first two leakage mechanisms are important, we emphasize the risks associated with the presence of abandoned wells. This is due to the large number and density of wells from a history of oil and gas exploration around the world, and the high degree of uncertainty surrounding the properties of these abandoned wells. With current proposed legislation in both the United States and Europe, a need is emerging for practical assessment of leakage risk. In order to accurately predict leakage of brine and CO₂ from the injection layer, the geological information for the injection site and the location and makeup of the man-made leakage pathways previously alluded to must be taken into account. Unfortunately, both the geology and abandoned well metadata are typically high in uncertainty, which must be accounted for. With such a high number of random variables, the current state of the art is running many realizations of a system, using a Monte Carlo approach. This requires that the underlying solution algorithms be accurate, and efficient. In the past, many researchers in both academia and industry have turned to robust numerical analysis packages used in the oil industry. However, due to the large range of scales important to this problem (domains of tens of kilometers on a side affected by leakage pathways with diameters of tens of centimeters) such modeling techniques become computationally expensive for all but the most basic analysis. A computational model developed at Princeton University, and currently being commercialized by Geological Storage Consultants, LLC has been shown to be efficient with sufficient accuracy to allow for comprehensive risk assessment of CO₂ injection projects. The model allows for mixing solution methods- using computationally expensive algorithms for formations of greater importance (e.g.- the injection formation) and more efficient, simplified algorithms in other areas of the domain. This ability to arbitrarily mix solution methods offers significant flexibility in the design and execution of models. This paper addresses the framework and algorithms used, and illustrates the importance of efficiency and parallelism using the case study of an injection site in Alberta, Canada. We show how the framework can be used for project planning, for risk mitigation (insurance), and for regulatory groups. Finally, the importance of flexible analysis tools that allow for efficient and effective management of computational resources is discussed.

5. Celia, Michael, Jan M. Nordbotten, , M. Dobossy, and Benjamin Court, 2009: Risk of Leakage versus Depth of Injection in Geological Storage. Energy Procedia, 1(1), doi:10.1016/j.egypro.2009.02.022 2573-2580
   [ Abstract ]

   One of the outstanding challenges for large-scale CCS operations is to develop reliable quantitative risk assessments with a focus on leakage of both injected CO₂ and displaced brine. A critical leakage pathway is associated with the century-long legacy of oil and gas exploration and production, which has led to many millions of wells being drilled. Many of those wells are in locations that would otherwise be excellent candidates for CCS operations, especially across many parts of North America. Quantitative analysis of the problem requires special computational techniques because of the unique challenges associated with simulation of injection and leakage in systems that include hundreds or thousands of existing wells over domains characterized by layered structures in the vertical direction and very large horizontal extent. An important feature of these kinds of systems is the depth of each well, and the fact that the number of wells penetrating different formations decreases as a function of depth. As such, one might reasonably expect the risk of leakage to decrease with depth of injection. With the special computational models developed to simulate injection and leakage along multiple wells, in layered systems with multiple formations, quantitative assessment of risk reduction as a function of injection depth can be made. An example of such a system corresponds to the Wabamun Lake area southwest of Edmonton, Alberta, Canada, where several large coal-fired power plants are located. Use of information about both the existing wells and the local stratigraphy allows a realistic model to be constructed. Leakage along existing wells is assumed to follow Darcy’s Law, and is characterized by a set of effective permeability values. These values are assigned stochastically, using several different methods, within a Monte Carlo simulation framework. Computational results show the clear trade-off between depth of injection and risk of leakage. The results also show how properties within the different formations affect the risk profiles. In the Wabamun Lake area, one of the formations has the highest injectivity, by far, while having a moderate number of existing wells. Its moderate risk of leakage, as compared to injections in formations above and below, shows some of the key factors that are likely to influence injection design for large-scale CCS operations.

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